Fertility affects directly and indirectly health. Within a family high fertility tends to imply less resources to devote to the health of each family member, in addition to any direct impact of a large number of pregnancies on the health of the woman and of her offspring. Macro effects also may be important. Large cohorts tend to fare less well in labor markets than small cohorts with the result that they tend to be less healthy because of relatively smaller incomes and greater stresses and frustrations due to un- and underemployment. Therefore understanding fertility determinants better leads to a better understanding of health determinants. Becker and Easterlin have proposed alternative economic models to explain fertility behavior. With relatively few assumptions these models can generate equations with identical variables, but with different parameters and different implications for policy. The models can be estimated with data on income or schooling and fertility drawn from two generations. Because of the previous absence of such data on income, however, no estimates are currently available. The first aim of this project is to estimate these equations using a new data set with the required data on intergenerational income as well as an existing data set with intergenerational information on nonincome variables. The assumptions can be weakened further by using data on cousins and a latent variable methodology to represent critical unobserved variables. The second aim of the project is to develop the necessary models and to use the special data on cousins in the two data set to estimate them. Both steps should help improve knowledge concerning the relevance of the competing economic models of fertility, with their differential implications for health and for policy.